The role of experience in echocardiographic identification of location and extent of mitral valve prolapse with 2D and 3D echocardiography

Contradiction exists on the incremental value of two-dimensional (2D) and 3D transoesophageal echocardiography (TOE) over 2D transthoracic echocardiography (TTE) for the detection of mitral valve (MV) prolapse in readers with different echocardiographic experience. Twenty patients and five healthy persons were retrospectively identified who had undergone 2D-TTE, 2D-TOE and 3D-TOE. Fifteen (75 %) patients had surgical evidence of prolapse of the posterior MV leaflet and five patients (25 %) had a dilated MV annulus without prolapse. Three reader groups with different echocardiographic expertise (novice, trainees, cardiologists) scored thus in total 675 posterior scallops. Overall there was an improvement in agreement and Kappa values from novice to trainees to cardiologists. Diagnostic accuracies of 2D-TOE were higher than those of 2D-TTE mainly in novice readers. The incremental value of 3D-TOE over 2D-TOE was mainly seen in specificities. Time to diagnosis was dramatically reduced from 2D to 3D-TEE in all reader groups (all P < 0.001). 3D-TOE also improved the agreement (+12 to +16 %) and Kappa values (+0.14 to +0.21) in all reader groups for the exact description of P2 prolapse. Differences between readers with variable experience in determining the precise localization and extent of the prolapsing posterior MV scallops exist in particular in 2D-TTE analysis. 3D-TOE analysis was extremely fast compared to the 2D analysis methods and showed the best diagnostic accuracy (mainly driven by specificity) with identification of P1 and P3 prolapse still improving from novice to trainees to cardiologists and provided optimal description of P2 prolapse extent

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe